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RESEARCH PAPER · Journal of Physics Materials · 2022

Reflections on one million compounds in the open quantum materials database (OQMD)

Jiahong Shen, Sean D. Griesemer, Abhijith Gopakumar, Bianca Baldassarri, James E. Saal, Muratahan Aykol, Vinay I. Hegde, Chris M. Wolverton

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Reflections on one million compounds in the open quantum materials database (OQMD)OriginalHeterogeneous catalysis mediated by light, electricity and enzyme via machine learning: Paradigms, applications and prospects24Machine-Learning-Assisted Understanding of Polymer Nanocomposites Composition–Property Relationship: A Case Study of NanoMine Database28Accuracy of DFT computed oxygen-vacancy formation energies and high-throughput search of solar thermochemical water-splitting compounds21Accurate prediction of semiconductor bandgaps based on machine learning and prediction of bandgaps for two-dimensional heterojunctions14Chalcopyrite thermochemistry: The simple salt approximation together with quantum DFT methods6Stability and Equilibrium Structures of Unknown Ternary Metal Oxides Explored by Machine-Learned Potentials29Accelerating the prediction of stable materials with machine learning104Exploiting redundancy in large materials datasets for efficient machine learning with less data118Oxygen Vacancy Formation Energy in Metal Oxides: High-Throughput Computational Studies and Machine-Learning Predictions60Composition-based phase stability model for multicomponent metal alloys3Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange52The Scaffolding Problem: How Materials AI Depends on Unstated Scientific Infrastructure0Advances in materials informatics: a review42Super-lattices enabled performances of vanadate-phosphate glass-ceramic composite cathode in lithium-ion batteries8Machine learning in energy storage material discovery and performance prediction77First-principles investigation of Cu/Ti-TM/Si (TM=W, Ru) interfaces: Role of Ti-TM binary alloys as diffusion barrier layers2Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange18Small basis set density functional theory method for cost-efficient, large-scale condensed matter simulations2Computational applications for the discovery of novel antiperovskites and chalcogenide perovskites: a review14Prediction of crystal structures and superconductivity of actinium borides at high pressures2Construction and application of materials database under data-driven research paradigm3Copper diffusion hindrance in Ti-TM (TM = W, Ru) alloys: A first-principles insight1Efficient structure-informed featurization and property prediction of ordered, dilute, and random atomic structures9Beyond chemical structures: lessons and guiding principles for the next generation of molecular databases8Integrated Sharing Platform for Genetic Data of Rare and Precious Metal Materials1MACHINE LEARNING IN NANOSCALE THERMAL TRANSPORT2Wide-ranging predictions of new stable compounds powered by recommendation engines12Artificial Intelligence and Machine Learning in Tribology: Selected Case Studies and Overall Potential36A generative model for inorganic materials design498The effect of phonon-phonon interaction in Ta based Heusler alloys for accurate phonon transport properties5Ultra-low lattice thermal conductivity in 18 VEC quaternary Heusler alloys—Efficient thermoelectric materials4Deep learning enhanced prediction of microwave dielectric constant of spinel ceramics eliminating manual feature engineering4CO2 capture with adsorption strategies: Achievements, challenges, and prospects36Understanding the role of non-analytical corrections in phonon transport and thermal conductivity in half-Heusler alloys3AI-driven design of powder-based nanomaterials for smart textiles: from data intelligence to system integration27Mixed-anion thermoelectrics: Advanced tuning of electron and phonon transport10AI-powered OLEDs: speeding up innovation in displays3Crystal Structure and Physical Properties of Novel Quaternary Intermetallics Th2MoX2C (X = Si, Ge)0Combining feature-based approaches with graph neural networks and symbolic regression for synergistic performance and interpretability6Machine Learning as a Catalyst in Advanced Materials Research and Development0Computational Discovery of Ultralow Thermal Conductivity in the Energy-Degenerate Polymorphic Crystal Family A 2 M 2 M ’ Q 40Materials Databases: Foundations of Modern Digital Materials12A comprehensive first-principles analysis of the dynamical, structural, mechanical, electronic and thermodynamic properties of full-Heusler alloys X 2MgSi (X = Ru, Rh, Pd)0Machine Learning and Domain Adaptation for Material Generalization in Electrocatalyst Evaluation: A Comprehensive Review2An Informatic Elucidation of Transition Metal Chalcogenide-Based Materials for Energy Storage and Harvesting0Machine Learning in Materials Science: Data-Driven Discovery and Functional Applications1Autonomous Materials Exploration Integrates Automated Phase Identification and AI Agents Enhanced by Human Guidance0A Machine Learning Approach for Predicting Passive Current Densities for Cr-Passivated Fe-Based Alloys as a Function of Physical, Chemical, and Metallurgical Conditions0

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